Towards a robust, real-time face processing system using CUDA-enabled GPUs

Bharatkumar Sharma, Rahul Thota, Naga Vydyanathan, Amit Kale
Siemens Corporate Technology, SISL – Bangalore, India
International Conference on High Performance Computing (HiPC), 2009


   title={Towards a robust, real-time face processing system using CUDA-enabled GPUs},

   author={Sharma, B. and Thota, R. and Vydyanathan, N. and Kale, A.},

   booktitle={High Performance Computing (HiPC), 2009 International Conference on},





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Processing of human faces finds application in various domains like law enforcement and surveillance, entertainment (interactive video games), information security, smart cards etc. Several of these applications are interactive and require reliable and fast face processing. A generic face processing system may comprise of face detection, recognition, tracking and rendering. In this paper, we develop a GPU accelerated real-time and robust face processing system that does face detection and tracking. Face detection is done by adapting the Viola and Jones algorithm that is based on the Adaboost learning system. For robust tracking of faces across real-life illumination conditions, we leverage the algorithm proposed by Thota and others, that combines the strengths of Adaboost and an image based parametric illumination model. We design and develop optimized parallel implementations of these algorithms on graphics processors using the Compute Unified Device Architecture (CUDA), a C-based programming model from NVIDIA. We evaluate our face processing system using both static image databases as well as using live frames captured from a firewire camera under realistic conditions. Our experimental results indicate that our parallel face detector and tracker achieve much greater detection speeds as compared to existing work, while maintaining accuracy. We also demonstrate that our tracking system is robust to extreme illumination conditions.
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